Two-stage estimation to adjust for treatment switching in randomised trials: A simulation study investigating the use of inverse probability weighting instead of re-censoring

Latimer, N. orcid.org/0000-0001-5304-5585, Abrams, K.R. and Siebert, U. (2019) Two-stage estimation to adjust for treatment switching in randomised trials: A simulation study investigating the use of inverse probability weighting instead of re-censoring. BMC Medical Research Methodology, 19. 69. ISSN 1471-2288

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Keywords: Treatment switching; Treatment crossover; Survival analysis; Overall survival; Oncology; Health technology assessment; Time-to-event outcomes; Prediction; Re-censoring; Inverse probability weighting
Dates:
  • Accepted: 14 March 2019
  • Published (online): 29 March 2019
  • Published: 29 March 2019
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > ScHARR - Sheffield Centre for Health and Related Research
Funding Information:
FunderGrant number
NATIONAL INSTITUTE FOR HEALTH RESEARCHPDF-2015-08-022
Depositing User: Symplectic Sheffield
Date Deposited: 28 Mar 2019 10:03
Last Modified: 24 Apr 2019 13:51
Status: Published
Publisher: BioMed Central
Refereed: Yes
Identification Number: https://doi.org/10.1186/s12874-019-0709-9

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